Diagnostic yield and financial implications of a nationwide electrocardiographic screening programme to detect cardiac disease in the young
Bibliographic record
Abstract
AIMS: There is limited information on the role of screening with electrocardiography (ECG) for identifying cardiovascular diseases associated with sudden cardiac death (SCD) in a non-select group of adolescents and young adults in the general population. METHODS AND RESULTS: Between 2012 and 2014, 26 900 young individuals (aged 14-35 years) were prospectively evaluated with a health questionnaire and ECG. Individuals with abnormal results underwent secondary investigations, the costs of which were being based on the UK National Health Service tariffs. Six hundred and seventy-five (2.5%) individuals required further investigation for an abnormal health questionnaire, 2175 (8.1%) for an abnormal ECG, and 114 (0.5%) for both. Diseases associated with young SCD were identified in 88 (0.3%) individuals of which 15 (17%) were detected with the health questionnaire, 72 (81%) with ECG and 2 (2%) with both. Forty-nine (56%) of these individuals received medical intervention beyond lifestyle modification advice in the follow-up period of 24 months. The overall cost of the evaluation process was €97 per person screened, €17 834 per cardiovascular disease detected, and €29 588 per cardiovascular disease associated with SCD detected. Inclusion of ECG was associated with a 36% cost reduction per diagnosis of diseases associated with SCD compared with the health questionnaire alone. CONCLUSION: The inclusion of an ECG to a health questionnaire is associated with a five-fold increase in the ability to detect disease associated with SCD in young individuals and is more cost effective for detecting serious disease compared with screening with a health questionnaire alone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".